Apparatus, devices and methods for in vivo imaging and diagnosis

ABSTRACT

Exemplary method and apparatus for diagnosing or characterizing an inflammation within an anatomical structure can be provided. For example, using at least one source arrangement, it is possible to provide at least one first electro-magnetic radiation to the anatomical structure at least one first wavelength in vivo. With at least one detector arrangement, it is possible to detect at least one second electro-magnetic radiation at least one second wavelength provided from the anatomical structure. The second radiation can be associated with the first radiation, and the first wavelength can be shorter than the second wavelength. The second radiation can be provided from the anatomical structure due to at least one change in the anatomical structure caused by the inflammation without providing an artificial fluorescence substance. At least one computer arrangement can be used to determine at least one characteristic of the structure based on the second radiation to diagnose or characterize the inflammation within the anatomical structure.

CROSS REFERENCE TO RELATED APPLICATIONS

This application relates to and claims the benefit and priority fromInternational Patent Application No. PCT/US2015/042283 filed on Jul. 27,2015, which relates to and claims priority from U.S. Provisional PatentApplication Ser. No. 62/029,007 filed on Jul. 25, 2014, the disclosuresof which are incorporated herein by reference in their entirety.

FIELD OF THE DISCLOSURE

The present disclosure relates to medical imaging, and more particularlyto exemplary embodiments of apparatus, method and apparatus for imagingand diagnosis, and even more particularly, e.g., for molecular imagingof inflammation and oxidative stress by near infrared autofluorescence(NIRAF).

BACKGROUND INFORMATION

Molecular imaging is drawing research attention, which can revealimportant molecular expressions in human body, such as, e.g.,inflammation¹, oxidative stress (see, e,g., Ref. 2), cellular signallingpathway (see, e,g., Ref. 3), enzyme activities (see, e,g., Ref. 4)²,etc. Molecular information can be important for the diagnosis of variousdiseases, such as cancer (see, e,g., Ref. 5), cardiovascular diseases(see, e,g., Ref. 6), neurodegenerative diseases (see, e,g., Ref. 7) andopthalmological diseases (see, e,g., Ref. 8). Clinically used medicalimaging tools such as Computed tomography (CT) (see, e,g., Refs. 9011),magnetic resonance imaging (MRI) (see, e,g., Refs. 12-16), ultrasound(IVUS) (see, e,g., Refs. 17 and 18), optical coherence tomography (OCT)(see, e,g., Refs. 19-22) can acquire morphological information ofanatomical structures, but are limited to a detection of molecularinformation. As clinically used function imaging tools, positronemission tomography (PET) (see, e,g., Ref. 23) and single-photonemission computed tomography (SPECT) (see, e,g., Ref. 24) rely onmedicinal radiopharmaceuticals, which are not aimed at detecting nativemolecular information of the anatomical structures either.

To image inflammation biomarkers on the tissue, e.g., exogenous reagentscan be employed to label different cellular receptors and molecularspecies inside human body, such as blood stream and luminal organs. Forexample, near infrared fluorescent (NIRF) dyes are specifically designedto label cells, chemicals and enzymes associated with inflammation, suchas macrophages (see, e,g., Ref. 25), fibrin (see, e,g., Ref. 26) andcysteine protease (see, e,g., Refs. 26 and 27). However, the toxicity,uptake and clearance of such reagents can cause high potential risk forthe safety and health of patients. The regulatory approval of exogenousreagents can be time consuming and significantly inhibits the clinicalapplication.

Endogenous imaging methods are also being investigated intensively, suchas ultraviolet/visible autofluorescence (see, e,g., Refs. 18-31), timeresolved fluorescence/fluorescence lifetime imaging (see, e,g., Refs.32-32), near infrared spectroscopy (NIRS)/diffusive reflectancespectroscopy (see, e,g., Ref. 36-39), and Raman spectroscopy (see, e,g.,Refs. 40-44). While these exemplary techniques can detect certainchemical information, such as, e.g., cholesterol, cholesterol ester,collagen, and elastin, they may not be sufficient to evaluate biomarkersof inflammation and oxidative stress. Therefore it is challenging tocorrelate the information provided by the above endogenous imagingmodalities with inflammation and oxidative stress directly.

Accordingly, there may be a need to address and overcome at least suchdeficiencies described herein above. For example, this can be done,e.g., by providing another (e.g., label free molecular) imaging modalityto detect an inflammation on the tissue.

SUMMARY OF EXEMPLARY EMBODIMENTS

To address and/or overcome the above-described problems and/ordeficiencies, exemplary embodiments of device, method and apparatus todetermine molecular information associated with important physiologicalevents such as inflammation and oxidative stress using near-infraredautofluorescence (NIRAF). For example, such apparatus, device and methodcan be employed for detecting vulnerable atherosclerotic plaques usingNIRAF.

According to an exemplary embodiment of the present disclosure,apparatus, devices and methods can be provided for detecting thepresence of native autofluorescence from anatomical features that havebeen modified by naturally occurring oxidative processes within the bodyincluding the process of inflammation.

For example, autofluorescence excited using light or otherelectro-magnetic radiation, in the red and near-infrared region of theoptical spectrum can be produced automatically in biological tissues orin the modification of biological tissues, where the modification can bea result of oxidative stress and inflammatory activity.

NIRAF can be generated by the optical absorption of light by biologicaltissues, which can then re-radiate the NIRAF light or otherelectro-magnetic radiation at a longer wavelength than the excitationlight.

One of exemplary features of NIRAF is that the radiation/output usedand/or produced thereby is provided in a wavelength region wherehemoglobin and water have low molecular absorption cross sections.

This exemplary feature facilitates a deeper penetration of NIRAFexcitation and better transmission of the returning NIRAF emission, andcan reduce the risk for biological tissue damage.

Due to a low optical absorption by water and hemoglobin, the NIRAFspectrum may provide a low amount of wavelength-dependent attenuation.NIRAF signal levels can be directly correlated with concentration of theautofluorescence moiety. Additional exemplary procedures, apparatus,devices and methods required to correct for the wavelength-dependence ofthe absorption, such as diffuse reflectance spectroscopy, to recover theintrinsic NIRAF spectrum may not be required to produce a diagnosticallyvalid result.

One exemplary feature of NIRAF is that a diagnostically valid result canbe achieved without the requirement for multiwavelength detection andadditional spectral processing methods.

An exemplary selection of NIRAF wavelength can reduce interferingfluorescence signals from structural proteins and other known biologicalautofluorescent molecules such as NADH and FAD. By using the exemplaryNIRAF procedure, it is possible to detect atherosclerotic plaquescontaining necrotic material with high sensitivity and specificityagainst lipid-rich, e.g., that is not necrotic, and otheratherosclerotic plaques.One exemplary feature of the NIRAF signal is that the signal can berelated to modifications of proteins and lipo-proteins through themechanism of oxidative stress.Dityrosine cross linkages can be one exemplary feature that can producethe NIRAF signal.

According to an exemplary embodiment of the present disclosure, theimplementation of the exemplary NIRAF procedures, apparatus, devices andmethods can be combined with other structural imaging modalities such asOCT, OFDI, SD-OCT, TD-OCT, SECM, SEE, photoacoustics, confocalendoscopy, ultrasound, angioscopy, bronchoscopy, colonoscopy, andeye-box. NIRAF data can be analyzed by intensity, spectral ratio, e.g.,between 2 or more bands, principal component analysis, linear leastsquares, wavelets transformation, support vector machines and/or neuralnetworks.

According to additional exemplary embodiments of the present disclosure,using the output of the NIRAF analysis, diagnostic predictions can beobtained using logistic regression, discriminant analysis, clusteranalysis, factor analysis, and other supervised and unsuperviseddecision tools.

Thus, exemplary method and apparatus for diagnosing or characterizing aninflammation within an anatomical structure according to an exemplaryembodiment of the present disclosure can be provided. For example, usingat least one source arrangement, it is possible to provide at least onefirst electro-magnetic radiation to the anatomical structure at at leastone first wavelength in vivo. With at least one detector arrangement, itis possible to detect at least one second electro-magnetic radiation atleast one second wavelength provided from the anatomical structure. Thesecond radiation can be associated with the first radiation, and thefirst wavelength can be shorter than the second wavelength. The secondradiation can be provided from the anatomical structure due to at leastone change in the anatomical structure caused by the inflammationwithout providing an artificial fluorescence substance. At least onecomputer arrangement can be used to determine at least onecharacteristic of the structure based on the second radiation todiagnose or characterize the inflammation within the anatomicalstructure.

According to another exemplary embodiment of the present disclosure,apparatus and method can be provided. For example, a catheter can beconfigured and structured to be inserted into a blood vessel. With anenergy source arrangement, it is possible to provide at least one firstlight radiation through the catheter to the blood vessel at least onefirst wavelength. In addition, with a detector arrangement, it ispossible to detect at least one second light radiation through thecatheter at least one second wavelength that is different from the firstwavelength. The second light radiation can be based on anautofluorescence of at least one portion of the blood vessel beingimpacted by the at least one first light radiation. Further, with acomputer arrangement, it is possible to determine at least onecharacteristic of the blood vessel based on the second light radiationto diagnose or characterize at least one characteristic of the bloodvessel.

According to yet another exemplary embodiment of the present disclosure,apparatus and method can be provided. For example, a catheter configuredand structured to be inserted into a blood vessel. With an energy sourcearrangement, through the catheter, at least one first light radiationcan be provided to the blood vessel at least one first wavelength thatis between 550 nm and 800 nm. With a detector arrangement, it ispossible to detect, through the catheter, at least one second lightradiation at least one second wavelength that is between 640 nm and 900nm. The second light radiation can be based on an autofluorescence of atleast one portion of the blood vessel being impacted by the first lightradiation. Further, with a computer arrangement, it is possible todetermine at least one of oxidative stress, calcium, intraplaquehemorrhage, protein modification, lipo-protein modification, lipidmodification, and/or enzymatic activity based on the second lightradiation.

In another exemplary embodiment of the present disclosure, the firstwavelength can be between 600 nm to 90 nm, between 600 and 800 nm,between 650 nm to 750 nm, and/or between 650 nm and 700 nm. The secondwavelength can be between 640 nm and 1000 nm, and/or between 640 nm and800 nm. The second wavelength can be selected to be outside a wavelengthrange of the background emission of a double clad fiber optic. An upperend of the wavelength range can be more than 20 nm or 40 nm. The secondwavelength can be a plurality of second wavelengths, and the detectioncan be performed as a function of the second wavelengths. The detectioncan include a mathematical manipulation of an emission spectrum of thesecond radiation to further specify the characterization of theinflammation.

As indicated herein, the characteristic can be at least one of oxidativestress, calcium, intraplaque hemorrhage, protein modification,lipo-protein modification, lipid modification, and/or enzymaticactivity. The protein modification can be dityrosine or nitrotyrosine,the lipo-protein modification can be oxidized LDL, the intraplaquehemorrhage can contain endogenous porphyrins. At least one thirdradiation can be provided to the sample and at least one fourthradiation to a reference. At least one fifth radiation that is aninterference between the third and fourth radiations can be received,and the determination can be performed as a further function of thefifth radiation. The first radiation can be at least partiallyco-localized with the first radiation.

In a further exemplary embodiment of the present disclosure, wherein thestructure can be a coronary artery. The first electro-magnetic can beprovided within the coronary artery. The coronary artery can be in apatient suspected of having necrotic plaque.

According to a still further exemplary embodiment of the presentdisclosure, the determination can be performed by detecting at least twosecond wavelength ranges, characterizing a spectral shape data or arelative intensity data with the at least two second wavelength ranges,and comparing the spectral shape or relative intensity data to atraining data set. The spectral shape data can be compared as a ratio ofthe second wavelength ranges. The spectral shape data or relativeintensity data can be calibrated with noise or sensor parameters. Thecharacterizing process can comprise analyzing with a principle componentanalysis method.

In yet another exemplary embodiment of the present disclosure, thedetermination can include detecting the plurality of second wavelengths,scoring a spectral shape and relative intensity with the secondwavelengths, and comparing a third score to a training data set.Further, the second radiation can be provided in a first range that isbetween 640 nm and 600 nm and in a second range that is between 660 nmand 900 nm, and the determination can comprise comparing a ratio of thefirst and second range to a training data set.

According to yet another exemplary embodiment of the present disclosure,an apparatus and method can be provided. For example, with an energysource, it is possible to provide at least one first light radiation toa structure at least one first wavelength. The wavelength can becontrolled to be between 400 nm and 900 nm. With a detector arrangement,it is possible to detect at least one second light radiation at leastone second wavelength which is different from the first wavelength. Thesecond light radiation can be based on an autofluorescence of at leastone portion of the structure being impacted by the first lightradiation. Further, with a computer arrangement, it is possible togenerate at least one first image of the portion(s) of the structure andat least one gradient second image based on the second light radiation.

For example, the first or second images can be co-registered. Thegeneration procedure can comprises obtaining an OCT image, an IVISimage, an angiographic image, a CT image, or an MRI image. The secondimage can include a display of a ratio of at least two wavelength rangesof the second light radiation.

In still a further exemplary embodiment of the present disclosure, anapparatus can be provided comprising a double clad fiber structure whichis configured to facilitate at least one of an optical coherencetomography and/or NIR fluorescence and transmit a fluorescence signal.The double clad fiber structure can include at least one core and atleast one cladding. A configuration of the core and the cladding can beis provided such that a ratio of the core to the cladding causes areduction or a minimization of a bending loss of the fluorescencesignal, and wherein the configuration further effectuates a reduction ora minimization of a background fluorescence. A computer can be providedwhich calibrates the fluorescence background signal based on thebackground fluorescence of the double clad fiber.

Exemplary embodiments of the present disclosure can be advantageous inthat there is no need to add an exogenous label. Generally, withfluorescence detection, the addition of an artificial or exogenousfluorescent moiety may be required, which can increase the time andcomplexity of a diagnostic or therapeutic procedure. According to theexemplary embodiments of the present disclosure, the use of dityrosineor other fluorophores found in an anatomical structure can facilitatediagnosis or characterization without the need to add an exogenousfluorescent moiety into the anatomical structure.

These and other objects, features and advantages of the exemplaryembodiments of the present disclosure can become apparent upon readingthe following detailed description of the exemplary embodiments of thepresent disclosure, when taken in conjunction with the appended claims.

BRIEF DESCRIPTION OF THE DRAWINGS

Further objects, features and advantages of the present disclosure willbecome apparent from the following detailed description taken inconjunction with the accompanying figures showing illustrativeembodiments of the present disclosure, in which:

FIG. 1 is a schematic block diagram of an exemplary embodiment of anear-infrared (NIR) auto-fluorescence arrangement/system according tothe present disclosure;

FIG. 2 is a flow diagram of an exemplary embodiment of the method tocollect, process and analyze data according to the present disclosure;

FIG. 3 is a graph of exemplary autofluorescence spectra of the presentdisclosure acquired by an exemplary NIRAF apparatus/system shown in FIG.1;

FIGS. 4(a)-4(l) is a set of illustrations of comparisons of grosspathology (FIGS. 4(a)-4(d)) and associated NIRAF map (FIGS. 4(i)-4(l))from four representative plaques, using the exemplary embodiments ofapparatus, device and method according to the present disclosure;

FIG. 5 is an graph providing an exemplary comparison of NIRAF intensitycollected from 67 atherosclerotic plaques;

FIG. 6(a)-6(b) are graphs providing exemplary results from a principalcomponent analysis of NIRAF spectra acquired from 67 atheroscleroticplaques;

FIG. 7 is scatter plot illustrating an exemplary pathologicalclassification scheme based on principal component analysis of allpathologies acquired from 67 atherosclerotic plaques;

FIG. 8 is a scatter plot illustrating the discrimination betweennecrotic core and pathological intimal thickening pathologies classifiedby principal component analysis using discriminant analysis to constructthe decision line, using the exemplary embodiments of the presentdisclosure;

FIG. 9 is another scatter plot illustrating an exemplary pathologicalclassification based applying principal component analysis applied toexemplary simulated spectral data at lower spectral using the exemplaryembodiments of the present disclosure;

FIG. 10 is a graph illustrating the position of the spectral bandrelative to the exemplary autofluorescence spectra obtained from plaquesclassified as necrotic core and pathological intimal thickening;

FIG. 11 is another scatter plot illustrating another pathologicalclassification scheme based on ratioing integrated spectral bandintensities using the exemplary embodiments of the present disclosure;

FIG. 12 is a graph illustrating the exemplary NIRAF signals levels fordifferent pathologies at two exemplary excitation wavelengths, using theexemplary embodiments of the present disclosure;

FIG. 13(a)-13(b) are images of the exemplary NIRAF and histological dataobtained from a fresh, unfixed thin-section using the exemplaryembodiments of the present disclosure;

FIG. 14(a)-14(b) are graphs illustrating the integrated signal andspectral ratio levels acquired from representative atheroscleroticplaques obtained from fresh, unfixed aortic thin-sections withcorrelated pathologies using the exemplary embodiments of the presentdisclosure;

FIG. 15(a)-15(d) are images illustrating the integrated intensity andprincipal component scores for the first three principal componentsobtained from fresh, unfixed aortic thin-sections using the exemplaryembodiments of the present disclosure;

FIG. 16(a)-16(b) are graphs illustrating the exemplary spectral changesto the autofluorescence when human aortic tissue is exposed to anoxidizing agent;

FIG. 17(a)-17(b) are graphs showing the exemplary spectral absorptionand emission differences of dityrosine, an strongly autofluorescentbiomarker of protein modification and oxidative stress;

FIG. 18 is a schematic block diagram of the exemplarydevice/system/apparatus according to yet another exemplary embodiment ofthe present disclosure;

FIG. 19(a)-19(b) is a set of graphs illustrating an exemplarymeasurement of NIRAF spectra from lipid rich plaques, calcified plaquesand fatty streak through a ball lens probe according to the exemplaryembodiment of the present disclosure;

FIG. 20 is a graph of an the exemplary result ratio of integratedautofluorescence and fiber background signals generated by two exemplaryNIRAF excitation wavelengths according to the exemplary embodiment ofthe present disclosure;

FIG. 21 shows a schematic block diagram of a multimodality OCT-NIRAFcatheter imaging system according to an exemplary embodiment of thepresent disclosure;

FIG. 22 shows a schematic block diagram of a NIRAF catheter imagingsystem with multichannel detection according to an exemplary embodimentof the present disclosure;

FIG. 23 shows a schematic block diagram of a NIRAF catheter imagingsystem with multiple dichroic mirrors for spectral ratio acquisition;

FIG. 24 shows a representative image of a 2D-NIRAF en face intensity mapaccording to an exemplary embodiment of the present disclosure;

FIG. 25(a)-25(b) is an exemplary composite OCT-NIRAF image and thecorresponding histology from obtained from a ruptured necrotic coreplaque according to an exemplary embodiment of the present disclosure;

FIG. 26 is a whisker box plot illustrating the NIRAF intensity obtainedthrough an intracoronary catheter for different pathologicalclassification;

FIG. 27 is an exemplary block diagram of an exemplary system inaccordance with certain exemplary embodiments of the present disclosure;and

FIG. 28 is an exemplary flow diagram of another method according to afurther exemplary embodiment of the present disclosure.

Throughout the figures, the same reference numerals and characters,unless otherwise stated, are used to denote like features, elements,components or portions of the illustrated embodiments. Moreover, whilethe subject disclosure will now be described in detail with reference tothe figures, it is done so in connection with the illustrativeembodiments. It is intended that changes and modifications can be madeto the described exemplary embodiments without departing from the truescope and spirit of the subject disclosure and appended claims.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

As shown in a diagram of FIG. 1, the exemplary device according to anexemplary embodiment of the present disclosure can be composed an energysource, e.g., a narrow band (0.1 nm) diode laser 110 emitted light at anexemplary wavelength of 740 nm. A lens assembly 115 can be used toproduce collimated light that can be passed through a short pass filter120 to remove spurious emission from the laser source, reflected off adichroic beam splitter filter 125 and focused by a second lens assembly130 onto the arterial specimen or another sample 140. The arterialspecimen is mounted on a computer controlled three-dimensional stagewith a temperature control device 150. The emitted light from thearterial specimen 140 is collected by the same lens assembly 130 in,e.g., a 180 degree backscattering geometry and approximately collimated,transmitted through a dichroic beamsplitter 125, focused by a secondlens assembly 160, which contains a long pass filter. The assembly 160focuses the emitted light into an optical detector 170. A computer 180(e.g., an exemplary embodiment of which is illustrated in a blockdiagram of FIG. 27) can control the motion of the stage and operation ofthe energy source 110, and can acquire and/or process the NIRAF signal.It should be understood that the tissue/sample described herein caninclude various anatomical structures and/or biological tissues such as,e.g., arterial tissue, blood vessels

FIG. 2 shows a flow diagram of an exemplary embodiment of the methodaccording to the present disclosure for data collection and processing,which can be implemented by the computer 180 shown in FIGS. 1 and 27. Inparticular, the exemplary method can be provided for collecting NIRauto-fluorescence and OFDI datasets. In general, fiduciary marks can beplaced at corners or the auto-fluorescence scan indicating the region ofinterest (ROI) after scanning the tissue. OFDI beam is aligned with theROI and scanned. Standard data processing methods/procedures can beemployed to condition the auto-fluorescence signal. NIRAF spectra areacquired from the luminal side in bulk measurement and unless otherwisenoted in the text. For example, according to the exemplary embodimentshown in FIG. 2, post-autopsy data can be obtained and pre-process(procedure 201). Then, OFDI beam can be aligned, and NIRAF Raster scanperformed (procedure 202). ROI can be labeled and an image/photographtaken (procedure 203). Histology can be performed (procedure 204).Further, dark detector noise and background can be removed (procedure205), and noise can be removed, e.g., using a low pass filter (procedure206). Peak intensity map can be generated (procedure 207) which can workin conjunction or together with the histology (procedure 204). Further.Principal component analysis and quadrant discrimination analysis(PCA/QDA) qualification can be performed, and PCA map can be formed(procedure 208), and compared to the histology.

FIG. 3 shows a graph of representative exemplary autofluorescencespectra obtained from different atherosclerotic pathologies using theapparatus, device and method according to exemplary embodiments of thepresent disclosure. The representative spectra, which are normalized tothe maximum intensity, can be obtained from specific sites located inintimal hyperplasia (IH), calcified (CA), pathological intimalthickening (PIT) and necrotic core (NC) plaques. Normalized spectra canillustrate a difference in spectral shape in the 760-820 nm region,which can indicate an exemplary change in the molecular compositionbetween plaque types.

FIGS. 4(a)-4(l) shows a set of illustrations comparing the grosspathology (top row—FIGS. 4(a)-4(d)) and associated NIRAF map (middlerow—FIGS. 4(e)-4(h)) to the preferable standard histology (bottom rowFIGS. 4(i)-4(l)) from 4 representative plaques, using the apparatus,device and method according to the exemplary embodiments according tothe present disclosure. For example, NIRAF intensity maps can benormalized to maximum intensity for the dataset. The following exemplaryfigures correspond to pathologies provided in this figure: intimalhyperplasia (see FIGS. 4(a), 4(e), 4(i)); fibrocalcific plaque (seeFIGS. 4(b), 4(f), and 4(j)); pathological intimal thickening (see FIGS.4(c), 4(g), 4(k)); necrotic core (see FIGS. 4(d), 4(h), 4(l)). Theseexemplary plaques can be diagnosed by histology.

FIG. 5 illustrates an exemplary graph providing an exemplary comparisonof NIRAF intensity among 67 plaques. For example, in this graph, thereare 13 necrotic core plaques, 21 pathological intimal thickening, 10fibrocalcific plaques, 9 intimal hyperplasia plaques, and 14 fibrousplaques. Using one way analysis of variance (ANOVA), the NIRAFintensities of NC, PIT and CA can be significantly different from IH andFB (p<0.0001). This can mean that NIRAF can differentiate differenttypes of plaques based on intensity information.

FIGS. 6(a) and 6(b) shows exemplary results obtained by applyingprincipal component analysis (PCA) to a data set composed of 67 plaquesaccording to exemplary embodiment of the present disclosure. In thisexample, autofluorescence spectra are preprocessed through normalizationbased on peak intensity (other normalization metrics may be employed)and then mean centered before applying the standard PCAalgorithm/procedure with the specially-programmed computer (e.g.,computer 180). Exemplary outputs of the PCA algorithm/procedure are thePCA scores (see FIG. 6(a)) and loading vectors or principal components(see FIG. 6(b)). In this example, the first two principal components orloading vectors can account for over 98% of the spectral variance. Thesecond principal component illustrates an exemplary feature betweenabout 760 nm and 820 nm, which likely agrees with the exemplary spectralshape variation.

FIG. 7 shows an exemplary scatter plot based on 1st and 2nd PCA scoresprovided using the apparatus, device and method according to theexemplary embodiments of the present disclosure, along with a tableproviding the exemplary results. For example, each type of plaques canhave a specific distribution. Using the quadrant discrimination analysis(QDA), e.g., the PCA score plane can be divided into, e.g., foursubspaces, representing four different categories: NC/PIT/CA/IH.Following an exemplary leave-one-out strategy, the sensitivity andspecificity can be analyzed to differentiate plaque types. See Table 1below for exemplary results.

TABLE 1 PCA-QDA classification of 4 plaque types Training set NC PIT CAFB Sensitivity Specificity NC(128 sites) 102 14 8 4 79.76% 95.06%PIT(332 sites) 49 264 3 16 79.50% 81.32% CA(84 sites) 0 1 83 0 98.81%99.8% FB(84 sites) 2 0 0 82 97.62% 99.6%

FIG. 8 illustrates another exemplary scatter plot based on first andsecond exemplary PCA scores providing differentiated necrotic core frompathological intimal thickening provided using the apparatus, device andmethod according to the exemplary embodiments of the present disclosure,along with a table providing the exemplary results. For example, theoverall exemplary accuracy can be about 85%. This analysis maydemonstrate diagnostic value to utilize NIRAF spectra to not only detectlipid rich plaques, but also evaluate their risk potential. In otherwords, this NIRAF analysis appears more sensitive to differentiation ofnecrotic core plaques than stable lipid rich plaques such aspathological intimal thickening and fatty streak than other exemplaryspectroscopic based technologies. See Table 2 below for exemplaryresults.

TABLE 2 PCA-QDA classification of NC and PIT Training set Classified asPIT Classified as NC Result PIT(332 sites) 281 51 SP = 84.6% NC(128sites) 19 109 SE = 85.2%

FIG. 9 shows an another exemplary scatter plot based on 1st and 2nd PCAscores of exemplary spectra data with reduced spectral resolutionprovided using the apparatus, device and method according to theexemplary embodiments of the present disclosure, along with a tableproviding the exemplary results. For example, each type of plaques canhave a specific distribution. Using a quadrant discrimination analysis(QDA), the PCA score plane can be divided into, e.g., four subspaces,representing four different categories: lipid (LPD)/erosion(ERO)/calcification (CA)/fibrous (FB). Following an exemplaryleave-one-out strategy, the sensitivity and specificity can be analyzedto differentiate plaque types. The results can show that the detectedintegrated spectral bandwidth of each channel can vary between 0.1 nm to10 nm without loss of diagnostic capability. See Table 3 below forexemplary results.

TABLE 3 PCA-QDA based on multichannel PMT LPD ERO CA FB LPD 39 0 1 0 ERO0 35 1 4 CA 9 0 31 0 FB 0 0 1 39

A spectral band ratio can provide an exemplary method to monitor thechanges in a set of NIRAF spectra without the requirement of spectral orstatistical models. The spectral band ratio is constructed byintegrating the intensity received in one spectral band having a definedspectral range by the integrated intensity of a second spectral bandwith its unique spectral range. FIG. 10 shows a graph illustrating theexemplary spectral integration regions compared to exemplary NIRAFspectra from representative necrotic core (NC) and pathological intimalthickening (PIT) plaques. In this example, the shorter wavelength band(blue channel) spans the wavelength region of 642-650 nm and the longerwavelength band (red channel) spans the region between 680-700 nm. Theintegrated signals from each exemplary spectral band can be divided toconstruct a spectral ratio, which can provide another example of thediagnostic contrast.

The spectral parameters that can be used to define the spectral bandscan be optimized to provide the most sensitive diagnostic criteria basedon changes in the spectra based on pathological state, presence ofspectral interferents and background emission. FIG. 11 shows a scatterplot illustrating an exemplary diagnostic algorithm based a comparisonof the integrated spectral intensity and the spectral ratio providedusing the apparatus, device and method according to the exemplaryembodiments of the present disclosure, along with a table providing theexemplary results. For example, a linear discriminant analysis can beapplied to generate a decision line that can discriminate betweennecrotic core and pathological intimal thickening pathologies. Theexemplary results show that the spectral parameters that define the blueand red bands discriminate between NC and PIT pathologies with highsensitivity and specificity. See Table 4 below for exemplary results.

TABLE 4 Double channel classification Training set Classified as NCClassified as PIT Parameters NC(128) 127 1 SE = 99.2% PIT(332) 14 318 SP= 95.7% Total (460) 141 319 Accuracy = 97.46%

Different excitation wavelengths in the near-infrared region can be usedto generate autofluorescence spectra whose spectral properties can beused to discriminate between different atherosclerotic plaques. Forexample, FIG. 12 shows a graph evaluating the exemplary tissue signallevels between two exemplary excitation wavelengths at 633 nm and 740 nmusing the apparatus, device and method according to the exemplaryembodiments of the present disclosure. In FIG. 12, the Y-axis isprovided in logarithmic scale. In this exemplary comparison ofexcitation-dependent signal strengths, the autofluorescence emissionintensities have been normalized by the wavelength-dependent spectralresponse of the spectrometer and detector. Both excitation wavelengthsillustrate similar NIRAF contrast among plaques. In addition, excitationlight at 633 nm can provide stronger exemplary tissue signal levels.

The excitation wavelength (first light radiation or firstelectro-magnetic radiation) which can be used to diagnose orcharacterize inflammation can be, for example, between 600 nm and 900nm, or between 600 nm and 850 nm, or between 620 nm and 770 nm, orbetween 630 nm and 750 nm, or between 650 nm and 700 nm. In otherembodiments the first wavelength is between 400 and 600 nm or between550 and 600 nm. This wavelength can be selected, for example, where theabsorption difference between necrotic core and normal tissue is largeor at an absorption peak of the necrotic tissue. For some embodiments,the excitation wavelength may be selected based on the absorbance of adifferent indicator tissue, such as pathological intimal thickeningtissue.

The wavelength being detected (e.g., the second light radiation, orsecond electro-magnetic radiation) is selected to, for example, optimizethe diagnostically relevant emission from the autofluorescent moiety andminimize background radiation-both from the tissue and from the fiberoptics. An exemplary emission has a wavelength range from 640 nm to 1000nm, up to 900 nm, or up to 800 nm. In some embodiments, the second lightradiation has a wavelength range from 640 nm to 800 nm or from 680 to770 nm. The 1000 nm upper limit is based on the sensitivity of the Sibased detectors and can be extended, for example, with the use ofInGaS-based detectors. Thus, for other detectors, a different upperlimit may be indicated. In some embodiments the second light radiationis selected to have a range of wavelengths that is greater than 20 nm orgreater than 40 nm. In some other embodiments, the second lightradiation is selected to have two, three, or more ranges of wavelengths.In some embodiments, the second light radiation is selected to omit thelocal minima of the Si background. For example, the second lightradiation may be selected so as to exclude the wavelengths at and around600 cm⁻¹ and/or 800 cm⁻¹.

NIRAF imaging can also be performed on histological thin-sections cutfrom fresh, unfixed arterial tissue whose thickness can be betweenapproximately 5-10 μm. FIGS. 13(a) and 13(b) show an exemplary image andan exemplary NIRAF integrated intensity map, respectively, generatedusing the apparatus, device and method according to the exemplaryembodiments of the present disclosure and a serially-cut thin-sectionthat has been stained with a standard histology stain, such asTrichrome. The exemplary NIRAF map is displayed in a linear grey scalewhere regions of high spectral intensity appear white. Exemplary NIRAFimaging allows autofluorescence spectra to be obtained from specificmorphological features. Registration between the NIRAF map and stainedhistology can allow spectral properties to be assigned to specificmorphological features, such as the thin-fibrous cap, necrotic coreregion, foam cells, macrophages, neutrophils, collagen and elastinfibers, cholesterol clefts, calcification and ceroid deposits. Theregion of high spectral intensity is assigned to the necrotic region ofa necrotic core plaque confirming that the autofluorescence observedfrom bulk tissue measurements is generated in the necrotic region wherethere are well established molecular-levels process responding to theinflammation and oxidative stress, such as modifications of proteins andlipids.

FIG. 14(a) shows a graph of the spectral band ratio that can begenerated, according to an exemplary embodiment of the presentdisclosure, from the analysis of the analysis of 16 thin sections ofdiffering pathologies. The error bar is one standard deviation, whereNC—nectroic core, PIT—pathological intimal thickening, IH—whole intimalhyperplasia and the intima and media regions can be reported from PITand NC plaques. Using one-way ANOVA, the intensity rank from high to lowis NC>Media>IH≈PIT>Intima. Although NC is very heterogeneous, itsintensity is significantly higher than the other four categories(p<0.01). Media has the second highest intensity, which is probably dueto densely aligned elastin and smooth muscle fibers. Extracellular lipidpool has similar NIRAF intensity to the intima and IH, which suggeststhat lipid deposition by itself does not contribute to NIRAF.

FIG. 14(b) shows a graph of the spectral band ratio, which can be usedby an exemplary method to assess the difference in spectral shapebetween different morphological features. For example, the spectralratio (blue/red) rank from high to low can be NC>PIT>Intima≈Media>IH. NCshows significantly stronger red shift than the other four categories(p<0.01). This agrees with observation from bulk tissue measurement. PIThas the second strongest red/blue ratio, which suggests that, as atransition between normal tissue and NC, PIT experiences certainchemical reactions and physiological processes, which lead to thegeneration of NIRAF fluorophore. Intima and media has similar red/blueratio, which agrees with the fact that they both have collagen andelastin as main components. IH is slightly lower than intima/media ofplaques. A possible reason can be that the inflammatory activitiespresent in NC and PIT might modify proteins and lipo-proteins in theintima and media.

FIGS. 15(a)-15(d) show a set of images illustrating exemplary resultsobtained by performing principal component analysis on allautofluorescence spectra collected from a thin-section of a necroticcore plaque using the apparatus, device and method according to theexemplary embodiment of the present disclosure. The exemplarythin-section was cut from frozen tissue without formalin fixation orparaffin embedding. Autofluorescence spectra were acquired using theexemplary embodiments according to the present disclosure. Spectra werebackground subtracted, normalized by length of the vector prior toapplying the PCA algorithm. For example, FIG. 15(a) is constructed fromintegrated spectra intensity and can show high intensity located inregions of both the necrotic core and media. The remaining images areconstructed from the scores resulting from the first three principalcomponents. The exemplary image in FIG. 15(b) is based on scores derivedfrom the first principal component. This exemplary image can clearlyoutline the necrotic core region and can also show focal high intensityregions. For example, the first principal component accounts for overabout 95% of the spectral variation. For comparison, PCA images based onthe second and third components, shown in FIG. 15(c) and FIG. 15(d)respectively, can also highlight spectral differences and togetheraccount for approximately 3% of the spectral variation. The PCA-derivedimages highlight morphological regions that can be related to variationsin the molecular compositional unlike the intensity based image.

FIGS. 16(a)-16(b) show a set of graphs that illustrate the exemplarychanges to the autofluorescence spectral properties generated using theapparatus, device and method according to the exemplary embodiments ofthe present disclosure. For example, an exemplary undiseased humanarterial section can be evenly divided into two halves where one half isincubated at approximately 37° C. for over 12 hours in 10% phosphatebuffered saline solution and where the second half is also incubated atthe same temperature for the same time in an oxidative solution composedof saturated manganese (III) acetate dissolved in 10% phosphate bufferedsaline solution. The NIRAF spectra of the specimens were collected priorto incubation (original) and after incubation (control and oxidized).NIRAF integrated intensities are compared in FIG. 16(a) where the errorbar indicates one standard deviation. The intensity of the original isnot homogenous as indicated in FIG. 16(a). The intensity of the oxidizedtissue exposed to manganese (III) acetate can be slightly higher thanthe control illustrating that the tissue autofluorescence can beincreased by oxidizing agents that modify proteins. NIRAF spectralratios are also compared in FIG. 16(b). The exemplary spectral ratioconstructed as red/blue shift illustrates the expected red-shift in theautofluorescence spectra of the oxidized relative to the control tissue.The fact that control sample presents a small spectral red shiftsuggests minor tissue degradation or oxidation occurs during theincubation period. However, the sample incubated in saturatedmanganese(III) acetate solution shows significantly stronger spectralred shift. This demonstrates that the NIRAF spectral properties can besensitive to the presence of oxidation products like proteinmodifications.

Dityrosine crosslinks are one of the well-established endogenousbiomarker for protein modifications and emits a strong autofluorescence.FIGS. 17(a)-17(b) show a set of graphs that illustrate the absorptionand autofluorescence spectral differences of dityrosine compared totyrosine and human atherosclerotic plaques. For example, dityrosine hasa maximum absorption at 280 nm and can have significant absorptionthrough the visible region where as tyrosine is limited to the UVabsorption (FIG. 17(a)). When excited at an exemplary excitationwavelength of 633 nm, fluorescence from dityrosine and autofluorescencefrom exemplary necrotic core (NC) and intimal hyperplasia (IH) plaquescan be compared in FIG. 17(b). The dityrosine spectrum appearssignificantly red-shifted and can account for the red-shifted emissionthan can be seen as atherosclerosis progresses.

In addition to dityrosine crosslinks, additionalmorphological/histological structures such as fibrin, fibrinogen,lipofuscin, ceroid can also generate NIRAF signals. Well known oxidativeproducts, such as chlorotyrosine, nitrotyrosine, bilirubin, billiverdin,4-hydroxy-2-nonenal, hydroxyiminiodihydropyrrole, and porphyrins, cancontribute to the NIRAF signal.

As shown in a diagram of FIG. 18, the exemplary device according to anexemplary embodiment of the present disclosure can be used to test dualclad fibers according to another exemplary embodiment of the presentdisclosure. This exemplary device/system shown in FIG. 18 can include anenergy/light/laser source 1810, which can be or include, e.g., a narrowband (0.1 nm) diode laser emitting light at an exemplary wavelength of,e.g., about 633 nm produced, e.g., by a helium:neon laser or anotherlight source. Collimated light from the source 1810 can pass through ashort pass filter 1815 to remove spurious emission from the lasersource, reflected off a dichroic beamsplitter filter 1820 and focused bya lens assembly 1825 into a double clad fiber ball lens probe 1830. Theback reflected and fiber-generated fluorescence can be collected by thesame lens 1830 in, e.g., a 180 degree backscattering geometry andcollimated, filtered by the dichroic beam splitter 1820 and long passfilter 1840 and is focused into a detector 1850, which can be a singlechannel detector, an array of detectors, and/or an f/2 NIR spectrometerequipped with a low-light level CCD. Computer control can beaccomplished using a computer 1860, which can be the aspecially-programmed computer described herein.

FIGS. 19(a)-19(b) shows a set of graphs illustrating an exemplarymeasurement of NIRAF spectra from representative necrotic core,calcified and fatty streak plaques through a double clad fiber ball lensprobe according to the exemplary embodiment of the present disclosure.The exemplary raw spectra are shown in FIG. 19(a). The extracted tissueNIRAF spectra are shown in FIG. 19(b), within exemplary emission windowof about 680-750 nm. Necrotic core plaques can have a much strongersignal than fiber background.

FIG. 20 shows a graph of the exemplary ratio of integratedautofluorescence intensities from representative lipid-containing (LPD),erosive (Erosive), calcified (CA) and fibrous (FB) atheroscleroticplaques generated by two exemplary wavelengths at 633 nm and 740 nm. Thetissue autofluorescence signal is integrated over the 680-750 nmspectral window to, e.g., exclude the strong silica Raman scatteringgenerated in the double clad fiber. The integration window was selectedto maximize the tissue autofluorescence to fiber background ratio.

NIRAF molecular imaging catheter system can be coupled with othermicrostructural imaging modalities that can provide a more comprehensiveview of the pathological state of the biological tissue. A schematicblock diagram of an exemplary embodiment of multimodality NIRAF imagingcatheter system according to the present disclosure is shown in FIG. 21.This exemplary apparatus of FIG. 21 can include, e.g., a microstructuralimaging system 2105 (which can generate images using one or moreprocessors, as described herein), a single mode optical fiber 2110, anenergy source, e.g., a near-infrared laser 2115, an optical fiber 2120,a dual-modality rotary junction 2125, a transparent imaging sheath 2130,a dual-modality optical imaging catheter 2135, a multimode fiber 2145,an optical detector 2150, data acquisition system 2155 and a dataprocessing and storage unit/arrangement 2160. It should be understoodthat a plurality of each of these described systems, arrangements andelements, or similar devices can be included and/or implemented in ortogether with the exemplary apparatus of FIG. 21.

The microstructural imaging system 2105 (e.g., one or more systemsimplementing one or more of optical frequency domain imaging, opticalcoherence tomography, spectrally encoded confocal microscopy, etc.modalities) can detect a back-reflected light from a tissue 2140 toacquire information and signals regarding tissue microstructures. TheNIRAF molecular imaging system can detect specific molecular informationfrom the tissue 2140. The microstructural imaging system 2105 can beconnected to the dual-modality rotary junction 2125 by the single modefiber 2110. A single mode or multimode fiber 2120 can be used to connectthe NIRAF laser 2115 to the dual-modality rotary junction 2125. Amultimode fiber 2145 can be a preferred optical fiber for connecting thedual-modality rotary junction 2125 to the optical detector 2150 for,e.g., the NIRAF molecular imaging modality to achieve a high lightthroughput.

The dual modality rotary junction 2125 can combine two different opticalbeams, and serve as the interface between the stationary imaging systemsto the rotating and translating imaging catheter 2135. The multimodalitycatheter can include a dual clad fiber 2165, driveshaft 2170, and distalfocusing optics 2175 enclosed in a transparent imaging sheath 2130. Theimaging sheath 2130 can be used to protect the imaging catheter 2135 andthe tissue 2140, while the imaging catheter 2135 rotates and translatesand performs a helical scanning of the tissue 2140. The optical imagingbeam 2143 can be focused by the dual-modality optical imaging catheter2135 onto the tissue 2140. Returning light signals from the tissue 2140are detected by the microstructural imaging system 2105 and the opticaldetector 2150 of the NIRAF molecular imaging system. Both NIRAF andmicrostructural 2105 systems can be synchronized, and the signals can beacquired simultaneously by the data acquisition system 2155. The dataprocessing and storage unit/arrangement/apparatus 2160 can record and/orprocess the data in a real-time for the proper operation, and forsubsequent visualization and analysis.

The NIRAF molecular imaging system has flexibility in the choice ofcomponents. The source 2115 (e.g., NIR laser source) can be operated ineither continuous wave or pulsed mode and can be coupled into either anoptical fiber 2120 that is either single or multimode. Fibers 2120, 2145should be selected to have low background emission, for e.g., to improvethe tissue signal to background signal ratio. The optical detector 2150can include an optical filter, an optical assembly, and either a singlechannel or multichannel detection. Single channel detection can includeuse of either a photodiode, avalanche photodiode or photomultipliertube, which can be a preferred embodiment. In the case of single channeldetection, the optical assembly can include a first lens to collimate,an intervening optical filter and a second lens to focus the light tothe detector. A second embodiment of the optical assembly can consist ofa first lens to collimate the light, a dispersing element, for e.g., aprism, or grating, etc., a second lens to focus the dispersed light anda slit to select the spectral bandwidth before optical detection.Multichannel detection schemes and/or configuration can include the useof a spectral dispersing element, for e.g., grating, prism, spectrometeror series of filters, etc, and optical detector. An embodiment of amultichannel detection scheme can include a spectrometer, grating orprism to disperse the NIRAF emission and a charge coupled detector(CCD), electron multiplying charge coupled devices (EMCCD), CMOS cameraor multichannel photomultipliers to detect it. A second embodiment is touse a series of dichroic filters arranged such that shortest wavelengthband is reflected first, followed by the next shortest band. Thesespectral bands are then detected by multiple single channel detectors.

It should be understood to one having ordinary skill in the art that,according to the exemplary embodiment of the present disclosure, theexemplary molecular imaging system 2105 can be coupled to and/orintegrated with other systems which can utilize non-optical imagingmodalities, including but not limited to ultrasound, ultrasound,photoacoustic imaging, etc. so as to improve the imaging and comparisonthereof.

A schematic diagram of an exemplary embodiment of NIRAF catheter systemaccording to another exemplary embodiment of the present disclosure isshown in FIG. 22. This exemplary apparatus can include a laser oranother source of electro-magnetic radiation 2210, optical rotaryjunction 2220, NIRAF catheter 2230, spectrometer 2260, multichanneldetector 2270 and data acquisition and storage system 2280. It should beunderstood that a plurality of each of these described systems,arrangements and elements, or those similar thereto can be includedand/or implemented in or together with the exemplary apparatus shown inFIG. 22.

For example, the source (e.g., a NIRAF laser (2210 laser can beconnected to the optical rotary junction 2220 by an optical fiber 2215,which can be single-mode or multimode. The optical rotary junction 2220can serve as the interface between the stationary imaging system to therotating and translating NIRAF catheter 2230. In the rotary junction2220, the light is collimated by a lens 2222, filtered by a dichroicmirror 2224 to remove spurious emission from the laser, focused by asecond lens 2226 into the NIRAF imaging catheter 2230. The NIRAFcatheter 2230 can include an optical fiber 2232, driveshaft 2234, anddistal focusing optics 2236 enclosed in a transparent imaging sheath2238. The optical fiber 2232 can be either a dual clad fiber or amultimode fiber. The imaging sheath 2238 can be used to protect theimaging catheter 2230 and the tissue 2240, while the NIRAF catheter 2230rotates and translates and performs a helical scanning of the tissue2240. The optical imaging beam 2242 can be focused by the NIRAF catheter2230 onto the tissue 2240. Returning light signals from the tissue 2240are returned through the optical rotary junction 2230, filtered by thedichroic mirror 2224, coupled by a third lens 2228 into a multimodefiber 2250, delivered to the spectrometer 2260 and detected amultichannel detector 2270. The multichannel detector 2270 can be orinclude a multichannel photomultiplier tube, a charge coupled device(CCD), an electron multiplying charge coupled device (EMCCD), and/orCMOS camera. The data processing and storage apparatus/system 2280 canbe connected to the multichannel detector 2270 and the optical rotaryjunction 2220. The data processing and storage apparatus/system 2280 canrecord and/or process the data in a real-time for the proper operation,and for subsequent visualization and analysis.

Exemplary calculations/determinations of the spectral ratio can beachieved using a multiple dichroic mirror and single channel detectorscheme where the position and width of the spectral band detected iscontrolled by the selection of the wavelength-dependent transmission andreflection properties of the dichroic mirror arranged in series. Aschematic diagram of another exemplary embodiment of NIRAF cathetersystem according to the present disclosure is shown in FIG. 23. Thisexemplary apparatus can include a laser or a source of electro-magneticradiation 2310, optical rotary junction 2320, NIRAF catheter 2330,multiple filter assembly, multiple single channel detectors 2370, 2372,2374 and data acquisition and storage system 2380. It should beunderstood that a plurality of each of these described systems,arrangements and elements, or those similar thereto, can be includedand/or implemented in and/or together with the exemplary apparatus shownin FIG. 23.

Similar to the exemplary embodiment shown in FIG. 22, the source (e.g.,a NIRAF laser) 2310 laser is connected to the optical rotary junction2320 by an optical fiber 2315, which can be either single-mode ormultimode. The optical rotary junction 2320 can serve as the interfacebetween the stationary imaging system to the rotating and translatingNIRAF catheter 2330. The optical imaging beam 2342 can be focused by theNIRAF catheter 2330 onto the tissue 2340. Returning light signals fromthe tissue 2340 are returned through the optical rotary junction 2330,coupled into a multimode fiber 2350, and delivered to multiple filterassembly. The multiple filter assembly can include a collimating lens2360, a long-pass filter 2362, a dichroic mirror at a shortestwavelength cutoff 2364, and a dichroic mirror at a longer wavelengthcutoff 2366. Each dichroic mirror 2364, 2366 can be paired with a singlechannel detector 2372, 2374 and an additional detector 2376, whichreceives the longest wavelengths. FIG. 23 illustrates an exemplary threechannel detection system. Nonetheless, it should be understood that itis possible to increase the number of channels by increasing the numberof filtering stages and detectors. The data processing and storageapparatus/system 2380 can be connected to the multiple detectors and theoptical rotary junction 2320. The data processing and storageapparatus/system 2280 can record and/or process the data in a real-timefor the proper operation, and for subsequent visualization and analysis.

FIG. 24 shows a representative imaging of a 2-D NIRAF en face intensitymap obtained from an exemplary human coronary artery using amultimodality OCT-NIRAF system and catheter as described herein withreference to the diagram of FIG. 21. In this example, a fresh explanthuman heart imaged within 24 hours after the harvest procedure was usedin the ex vivo imaging study. Before OCT-NIRAF imaging, the lumen wasflushed with 10% phosphate buffered saline solution to facilitatecatheter access and to maintain the natural diameter of the coronarylumen. The x-axis of the 2D NIRAF intensity map corresponds to thelongitudinal pullback position, and the y-axis, the scanning angle(i.e., 0 to 360 degrees). In the image, the dashed line corresponds tointimal hyperplasia while the dotted line is a calcified plaque. Thevertical axis is the imaging angle (0 to 360 degrees) and the horizontalaxis is the pullback direction (0 to 50 mm). Image orientation is distal(left side) to proximal (right side) portion of the vessel. The colormap ranges from blue (low NIRAF intensity) to green, yellow and white(highest NIRAF intensity).

FIGS. 25(a) and 25(b) illustrate a set of exemplary images of acomposite OCT-NIRAF image extracted from a comprehensively scannedcoronary artery and the corresponding histology section for a rupturednecrotic core plaque. The OCT-NIRAF image was generated using amultimodality OCT-NIRAF system and catheter as described herein andshown in FIG. 21. In the exemplary OCT-NIRAF image (see FIG. 25(a)), theOCT image indicates the presence of a plaque rupture (arrow) and area ofhigh attenuation suggestive of a lipid pool or necrotic core (star). TheNIRAF signal is high at over the necrotic core location with goodcontrast. In the corresponding histology image (see FIG. 25(b)), the H&Estained section confirms that the plaque is a ruptured thin-cappedfiberatheroma. The scale bars for both images are 1 mm. This exemplaryresult can demonstrate co-registered intracoronary OCT and NIRAF imagingin living human patients undergoing percutaneous catheterization as astandard of care and provides microstructural and fluorescence imagingof biomarkers related to inflammatory responses and oxidative stress.

FIG. 26 shows a whisker box plot of the exemplary representation of thecatheter-based NIRAF signal intensities for different coronary lesiontypes including necrotic core (NC), pathological intimal thickening(PIT), calcification (CA) and intimal hyperplasia (IH). NIRAFintensities were acquired from diseased human coronary arteries ex vivousing as described using a multimodality OCT-NIRAF system and catheteras described herein and shown in FIG. 21. NIRAF intensities from NC,PIT, CA and IH, were statistically significantly different according toone-way ANOVA (p<0.0005). Using a Student's t-test, the NIRAF intensityof NC plaques was significantly higher than those from non-necroticlesions (p<0.0005). Calcified plaques in the coronary arteries showedslightly higher NIRAF than PIT. One possible reason for this finding isthat the calcified coronary plaques in this study were advanced andcoexisted with significant extracellular lipid. These results indicatethat NIRAF can differentiate NC and non-NC plaques (CA and PIT) incoronary arteries

In addition, the exemplary embodiments of the present disclosure can beused for analysis and/or treatment of other disease, including, e.g.,cancer and neurogenerative diseases.

FIG. 27 shows a block diagram of an exemplary embodiment of a systemaccording to the present disclosure. For example, exemplary proceduresin accordance with the present disclosure described herein can beperformed by a processing arrangement and/or a computing arrangement2702. Such processing/computing arrangement/system 2702 can be, forexample, entirely or a part of, or include, but not limited to, acomputer/processor 2704 that can include, for example, one or moremicroprocessors, and use instructions stored on a computer-accessiblemedium (e.g., RAM, ROM, hard drive, or other storage device).

As shown in FIG. 27, for example, a computer-accessible medium 2706(e.g., as described herein above, a storage device such as a hard disk,floppy disk, memory stick, CD-ROM, RAM, ROM, an optical disk (such as acompact disc (CD), digital versatile disc (DVD), or Blu-ray Disc (BD)™),a flash memory device, a memory card, and the like, etc., or acollection thereof) can be provided (e.g., in communication with theprocessing arrangement 2702). The computer-accessible medium 2706 cancontain executable instructions 2708 thereon. In addition oralternatively, a storage arrangement 2710 can be provided separatelyfrom the computer-accessible medium 2706, which can provide theinstructions to the processing arrangement 2702 so as to configure theprocessing arrangement to execute certain exemplary procedures,processes and methods, as described herein above, for example.

Further, the exemplary processing arrangement 2702 can be provided withor include an input/output interface/arrangement 2714, which caninclude, for example, a wired network, a wireless network, the internet,an intranet, a data collection probe, a sensor, etc. An I/Ointerface/arrangement 2714 can be used to provide communicationinterfaces to input and output devices, which may include a keyboard, adisplay, a mouse, a touch screen, touchless interface (e.g., a gesturerecognition device) a printing device, a light pen, an optical storagedevice, a scanner, a microphone, a camera, a drive, communication cableand a network (either wired or wireless). As shown in FIG. 27, theexemplary processing arrangement 2702 can be in communication with anexemplary display arrangement 2712, which, according to certainexemplary embodiments of the present disclosure, can be a touch-screenconfigured for inputting information to the processing arrangement inaddition to outputting information from the processing arrangement, forexample. Further, the exemplary display 2712 and/or a storagearrangement 2710 can be used to display and/or store data in auser-accessible format and/or user-readable format.

A detector interface can also be provided to work with the I/Ointerfaces to input and output devices. The detector may include, forexample a photomultiplier tube (PMT), a photodiode, an avalanchephotodiode detector (APD), a charge-coupled device (CCD), multi-pixelphoton counters (MPPC), or other. Also, the function of detector may berealized by computer executable instructions (e.g., one or moreprograms) recorded on the computer-accessible medium 2706.

According to yet another exemplary embodiment of the present disclosure,an apparatus and method can be provided, as shown in a flow diagram ofFIG. 28. For example, with an energy source, it is possible to provideat least one first light radiation to a structure at least one firstwavelength (procedure 2810). The wavelength can be controlled to bebetween 400 nm and 800 nm (procedure 2820). With a detector arrangement,it is possible to detect at least one second light radiation at leastone second wavelength which is different from the first wavelength(procedure 2830). The second light radiation can be based on anautofluorescence of at least one portion of the structure being impactedby the first light radiation. Further, with a computer arrangement, itis possible to generate at least one first image of the portion(s) ofthe structure and at least one gradient second image based on the secondlight radiation (procedure 2840).

For example, the first or second images can be co-registered. Thegeneration procedure can comprises obtaining an OCT image, an IVISimage, an angiographic image, a CT image, or an MRI image. The secondimage can include a display of a ratio of at least two wavelength rangesof the second light radiation.

The foregoing merely illustrates the principles of the disclosure.Various modifications and alterations to the described embodiments willbe apparent to those skilled in the art in view of the teachings herein.Indeed, the arrangements, systems and methods according to the exemplaryembodiments of the present disclosure can be used with and/or implementany OCT system, OFDI system, SD-OCT system or other imaging systems, andfor example with those described in International Patent ApplicationPCT/US2004/029148, filed Sep. 8, 2004 which published as InternationalPatent Publication No. WO 2005/047813 on May 26, 2005, U.S. patentapplication Ser. No. 11/266,779, filed Nov. 2, 2005 which published asU.S. Patent Publication No. 2006/0093276 on May 4, 2006, and U.S. patentapplication Ser. No. 10/501,276, filed Jul. 9, 2004 which published asU.S. Patent Publication No. 2005/0018201 on Jan. 27, 2005, and U.S.Patent Publication No. 2002/0122246, published on May 9, 2002, thedisclosures of which are incorporated by reference herein in theirentireties. It will thus be appreciated that those skilled in the artwill be able to devise numerous systems, arrangements and methods which,although not explicitly shown or described herein, embody the principlesof the disclosure and are thus within the spirit and scope of thepresent disclosure. In addition, to the extent that the prior artknowledge has not been explicitly incorporated by reference hereinabove, it is explicitly being incorporated herein in its entirety.Further, the exemplary embodiments described herein can operate togetherwith one another and interchangeably therewith. All publicationsreferenced herein above are incorporated herein by reference in theirentireties.

EXEMPLARY REFERENCES

The following references are hereby incorporated by reference in theirentireties:

-   1. Signore A, Mather S J, Piaggio G, Malviya G and Dierckx R A.    Molecular Imaging of Inflammation/Infection: Nuclear Medicine and    Optical Imaging Agents and Methods. Chemical Reviews. 2010;    110:3112-3145.-   2. Su H S, Nahrendorf M, Panizzi P, Breckwoldt M O, Rodriguez E,    Iwamoto Y, Aikawa E, Weissleder R and Chen J W. Vasculitis:    Molecular Imaging by Targeting the Inflammatory Enzyme    Myeloperoxidase. Radiology. 2012; 262:181-190.

What is claimed is:
 1. An apparatus, comprising: a catheter configuredand structured to be inserted into a blood vessel; an energy sourcearrangement configured to provide at least one first light radiationthrough the catheter to the blood vessel at least one firstnear-infrared wavelength; a detector arrangement configured to detect atleast one second light radiation through the catheter at least onesecond near-infrared wavelength that is different from the at least onefirst wavelength, wherein the at least one second light radiation isbased on an autofluorescence of at least one portion of the blood vesselbeing impacted by the at least one first light radiation; and a computerarrangement configured to determine at least one characteristic of theblood vessel indicative of inflammation based on the autofluorescenceand not based on a signal from an exogenous label, the determiningprocedure including a mathematical manipulation of the detector signalbased on the second light radiation to further determine the at leastone characteristic.
 2. The apparatus of claim 1, wherein the at leastone characteristic of the blood vessel indicative of inflammationcomprises an intraplaque hemorrhage.
 3. A method comprising: inserting acatheter into a blood vessel; providing, through the catheter, at leastone first light radiation to the blood vessel at at least one firstwavelength that is between 550 nm and 900 nm; detecting, through thecatheter, at least one second light radiation at least one secondwavelength that is between 640 nm and 900 nm, wherein the at least onesecond light radiation is based on an autofluorescence of at least oneportion of the blood vessel being impacted by the at least one firstlight radiation; and determining, based on the autofluorescence and notbased on a signal from an exogenous label, at least one characteristicof the blood vessel indicative of inflammation, the determiningprocedure including a mathematical manipulation of the detected signalbased on the at least one second light radiation to further determinethe at least one characteristic, and the at least one characteristiccomprising at least one of oxidative stress, calcium, intraplaquehemorrhage, protein modification, lipo-protein modification, lipidmodification, or enzymatic activity.
 4. The method according to claim 3,wherein the first wavelength is between 600 nm and 700 nm.
 5. The methodaccording to claim 3, wherein the mathematical manipulation includesbackground subtraction of the detector signal and normalization.
 6. Themethod according to claim 3, wherein the protein modification isdityrosine or nitrotyrosine.
 7. The method according to claim 3, whereinthe lipo-protein modification is oxidized LDL.
 8. The method accordingto claim 3, wherein the intraplaque hemorrhage contains endogenousporphyrins.
 9. The method according to claim 3, further comprisingproviding at least one third radiation to the sample and at least onefourth radiation to a reference, and receiving at least one fifthradiation that is an interference between the third and fourthradiations, wherein the determination is performed as a further functionof the fifth radiation.
 10. The method according to claim 9, wherein thefifth radiation is at least partially co-localized with the firstradiation.
 11. The method according to claim 3, wherein the blood vesselis in a patient suspected of having necrotic plaque.
 12. The methodaccording to claim 3, wherein determining procedure comprises: detectingat least two second wavelength ranges, characterizing a spectral shapedata or a relative intensity data with the at least two secondwavelength ranges, and comparing the spectral shape or relativeintensity data to a training data set.
 13. The method according to claim12, wherein the spectral shape data is compared as a ratio of the atleast two second wavelength ranges.
 14. The method according to claim12, wherein the spectral shape data or the relative intensity data arecalibrated with noise or sensor parameters.
 15. The method according toclaim 12, wherein the characterizing process comprises analyzing with aprinciple component analysis method.
 16. The method according to claim3, wherein the determining procedure comprises: detecting the pluralityof second wavelengths; scoring a spectral shape and relative intensitywith the second wavelengths, and comparing a third score to a trainingdata set.
 17. The method of claim 3, wherein the at least onecharacteristic of the blood vessel indicative of inflammation comprisesan intraplaque hemorrhage.
 18. An apparatus, comprising: a catheterconfigured and structured to be inserted into a blood vessel; an energysource arrangement configured to provide, through the catheter, at leastone first light radiation to the blood vessel at least one firstwavelength that is between 550 nm and 800 nm; a detector arrangementconfigured to detect, through the catheter, at least one second lightradiation at least one second wavelength that is between 640 nm and 900nm, wherein the at least one second light radiation is based on anautofluorescence of at least one portion of the blood vessel beingimpacted by the at least one first light radiation; and a computerarrangement configured to determine at least one characteristic of theblood vessel indicative of inflammation based on the autofluorescenceand not based on a signal from an exogenous label, the determiningprocedure including a mathematical manipulation of the detected signalbased on the at least one second light radiation to further determinethe at least one characteristic, and the at least one characteristiccomprising at least one of oxidative stress, calcium, intraplaquehemorrhage, protein modification, lipo-protein modification, lipidmodification, or enzymatic activity.
 19. The apparatus of claim 18,wherein the at least one characteristic of the blood vessel indicativeof inflammation comprises an intraplaque hemorrhage.
 20. An imagingmethod, comprising: providing at least one first light radiation to astructure at least one first wavelength that is between 600 and 900 nm;detecting at least one second light radiation at least one secondwavelength which is different from the first wavelength, wherein thesecond light radiation is based on an auto fluorescence of at least oneportion of the structure being impacted by the first light radiation;and generating at least one first image of the at least one portion ofthe structure and at least one gradient second image based on theautofluorescence and not based on a signal from an exogenous label,wherein the at least one first image or the at least one gradient secondimage includes information identifying at least one characteristicindicative of inflammation in the at least one portion of the structure,wherein the at least one characteristic indicative of inflammation isdetermined using a mathematical manipulation of the detected signalbased on the at least one second light radiation to further determinethe at least one characteristic.
 21. The imaging method of claim 20,wherein at least one of the first image or the at least one gradientsecond image is co-registered.
 22. The imaging method of claim 20,wherein the generation procedure comprises obtaining an OCT image, anIVIS image, an angiographic image, a CT image, or an MRI image.
 23. Theimaging method of claim 20, wherein the at least one gradient secondimage includes a display of a ratio of at least two wavelength ranges ofthe second light radiation.
 24. The imaging method of claim 20, whereinthe at least one characteristic indicative of inflammation in the atleast one portion of the structure comprises an intraplaque hemorrhage.